If you cannot attend I believe there will be a video recording that will be made available shortly after the event.

This workshop is a hands-on guide to extracting and analyzing a social network graph (with NO programming). Using examples from Twitter, YouTube, Email, flickr, and participant submissions, we will review the steps needed to take a network graph from collection through analysis and visualization to insight. Learn to tell stories about key people and groups with network visualizations. Participants will receive an introduction to social network analysis and NodeXL; be able to import network data; create a network map; and generate an actionable insight from a network map.

NodeXL allows users to generate network maps by importing data from Microsoft Office Excel. Participants are encouraged to download NodeXL prior to the workshop and bring a laptop and data sets when they attend to use during the workshop.

Thinking by seeing.- Visualizing networks: pictures of collections of connections.

Networks are everywhere: biological, commercial, social, technical. How to extract the networks around you: how to build your own “edge list”.

Living in a sea of tweets, links, likes, views, reads, ratings, reviews, comments, connections, tags, ties, edits, plays, check-ins, contacts, friends, follows, favorites, Networks are newly self-documenting: machine readable connections now comprise the majority of our connections with one another, making our social worlds more available to analysis than ever before.

Introduction to NodeXL: mechanics of getting a graph open, analyzed and visualized.

Hands-on: how to analyze a social graph. Using examples from Twitter, YouTube, Email, flickr, and participant submissions, we take a graph from collection through analysis and visualization. Telling stories about key people and groups with network visualizations.

Afternoon session:

Extracting networks that matter to your organization: defining the nature of the nodes and edges in a graph is the fundamental question in network analysis. Who are the people, organizations, processes, entities that matter to you and how are they tied, connected, or linked? How to query your existing logs and data sets to extract useful network graphs.

Decorating network graphs: using size, color, transparency, visibility, images, and location to better tell a story with a network graph.

Filtering a network: revealing key structures and nodes. Use dynamic filters to remove edges and nodes from the graph to reveal only those who meet specific criteria. Use a range of attributes to limit the graph to remove clutter and occlusion.

Scheduling regular data collection with NodeXL. A guide to using the free and open data collector to schedule the creation of network data sets on a regular automatic basis.